Structure-Preserving Unpaired Image Translation to Photometrically Calibrate JunoCam with Hubble Data
This enables quantitative analysis of Jupiter's atmospheric dynamics for planetary science, though it is incremental as it adapts existing methods to a specific domain problem.
The paper tackled the problem of photometrically calibrating JunoCam images of Jupiter using Hubble Space Telescope data by developing a structure-preserving unpaired image-to-image translation method, achieving improved retention of high-frequency features essential for atmospheric analysis.
Insights into Jupiter's atmospheric dynamics are vital for understanding planetary meteorology and exoplanetary gas giant atmospheres. To study these dynamics, we require high-resolution, photometrically calibrated observations. Over the last 9 years, the Juno spacecraft's optical camera, JunoCam, has generated a unique dataset with high spatial resolution, wide coverage during perijove passes, and a long baseline. However, JunoCam lacks absolute photometric calibration, hindering quantitative analysis of the Jovian atmosphere. Using observations from the Hubble Space Telescope (HST) as a proxy for a calibrated sensor, we present a novel method for performing unpaired image-to-image translation (I2I) between JunoCam and HST, focusing on addressing the resolution discrepancy between the two sensors. Our structure-preserving I2I method, SP-I2I, incorporates explicit frequency-space constraints designed to preserve high-frequency features ensuring the retention of fine, small-scale spatial structures - essential for studying Jupiter's atmosphere. We demonstrate that state-of-the-art unpaired image-to-image translation methods are inadequate to address this problem, and, importantly, we show the broader impact of our proposed solution on relevant remote sensing data for the pansharpening task.